The Question

A Day in the Life: How the Sept. 11 TweetMap Was Created

Yesterday we showed you Chris Whong’s tweet map from September 11th, 2012. Here’s how he did it:

A Day in the Life is a dump of 15,000 geocoded tweets, all from a single day, all from the five boroughs of New York City. Created by NYU Urban Planning Student and civic techie Chris Whong, the map is labeled a social media experiment, a visualization of social media interactions that allows a user to freely explore the city and see who was tweeting what, and most interestingly, where they tweet from. Our online social networks tend to mirror our real world networks, and A Day in the Life offers a peek into thousands of other networks that share the Urban Landscape, even if their many nodes and linkages don’t cross paths often (online or in real life).

The addition of latitude and longitude coordinates to the normal tweet data has some powerful implications, and adds a spatial element to the typical analysis of tweets by keyword or hashtag, and even see the movement of individual tweeters around the city over the course of the day (provided they tweet regularly of course). A Day in the Life is meant more for exploration, but other static maps and visualizations of links and specific keywords can be produced from the same types of data sets. (Eric Fischer released a series of maps highlighting movement corridors through cities using geocoded tweets earlier this year) The New York map is based on a similar one for Baltimore (http://www.charmcitynetworks.com/bmoretweets) that also features layers for Census data and Baltimore’s Vacant properties, giving the user some context for the location of the tweeter.

Interesting? Yes. Entertaining? Of course! Alarming? Sometimes (tweets about violence, drug use, truancy, etc can be seen here and there), but is this data really useful for drawing real conclusions about a city and effecting change? Maybe. It should be noted that this collection represents only a small sample of all tweets, 2-4% by some estimates. While there is certainly a broad geographic representation, with no corner of the city left out, the only people on these maps are those who had location services on, and the picture might be very different if all tweets were considered. Those who tweet their location, for whatever reason, may not be a representative sample of all tweeters.

The data source for these maps is Twitter’s streaming API, which allows a user to specify a bounding box. Any geocoded tweets that occur within the box are sent in real-time, and can be stored in a database for future use. The Baltimore Map was a result of impromptu civic hacktivism born on a Facebook group called Baltimore tech. Dave Troy, a local tech entrepreneur and urbanist wrote a script to pull Baltimore tweets from the API, and then published a link to the data for any who could find something useful to do with it. The results included animations of user movement overs time, aggregate tweet trail maps that highlight frequently traveled routes, word clouds that attempt to highlight themes, A Day in the Life, and more. So, we used Facebook connections to do twitter data analysis. Social Media begets Social Media.